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Bhavarth Bhangdia

Vetted Talent

Bhavarth Bhangdia

Vetted Talent

As a Data Science Intern at Alphaa AI, where I create impactful solutions using Python, Kaggle notebooks, and mathematical and statistical principles. I have proficiency in creating diverse datasets, architecting robust pipelines, and optimizing ETL processes for enhanced efficiency and data handling. I also convey complex ideas through compelling data stories, demonstrating my communication and visualization skills.


I am pursuing my Bachelor of Technology in Electronics and Communication Engineering from the Indian Institute of Information Technology Allahabad, with coursework in Data Structures, Operating Systems, Distributed Systems, and Machine Learning. I have skills in front-end and back-end development, using languages such as C++, JavaScript, and SQL, and frameworks like ReactJS, NodeJS, and MongoDB. I have spearheaded the development and launch of dynamic websites and applications, such as Filmpire CineVerse and Media Mimic, that enhance user engagement and streamline content discovery processes. I have solved over 500+ challenging problems on platforms like LeetCode, InterviewBit, and Code Studio, reflecting my dedication to honing problem-solving skills.


I am driven by a quest for excellence, constantly seeking to stay updated with the latest industry trends and best practices. I am eager to bring my technical expertise, passion for innovation, and collaborative spirit to a forward-thinking team.

  • Role

    ML ENGINEER

  • Years of Experience

    1.4 years

Skillsets

  • JavaScript
  • SQL
  • Python
  • AWS
  • diffusion model
  • Git
  • jax
  • Keras
  • opencv
  • Pytorch
  • Ray Serve
  • TensorFlow
  • Torch
  • Transformer

Vetted For

10Skills
  • Roles & Skills
  • Results
  • Details
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    Machine Learning Scientist II (Places) - RemoteAI Screening
  • 62%
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  • Skills assessed :Large POI Database, Text Embeddings Generation, ETL pipeline, LLM, Machine Learning Model, NLP, Problem Solving Attitude, Python, R, SQL
  • Score: 56/90

Professional Summary

1.4Years
  • Aug, 2024 - Present 10 months

    ML ENGINEER

    PIXLR
  • Dec, 2023 - Mar, 2024 3 months

    AI CODER

    SCALE AI
  • Sep, 2023 - Dec, 2023 3 months

    DATA SCIENCE INTERN

    ALPHAA AI
  • May, 2023 - Jul, 2023 2 months

    SOFTWARE DEVELOPER INTERN

    AITA

Applications & Tools Known

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    Javascript

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    React

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    Node.js

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    Next.js

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    Express.js

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    Python

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    PyTorch

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    BigPanda

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    MySQL

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    Git

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    Docker

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    OpenShift

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    Kubernetes

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    Azure DevOps

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    Postman

Work History

1.4Years

ML ENGINEER

PIXLR
Aug, 2024 - Present 10 months
    Led research and development of AI systems in Image Processing using LoRA finetuning. Designed inference pipelines optimizing runtime by 70%. Implemented MLOps pipelines with Ray Serve, improving model serving stability by 120%. Reduced text-to-image generation latency by 75%.

AI CODER

SCALE AI
Dec, 2023 - Mar, 2024 3 months
    Evaluated AI-generated code quality, improving readability and maintainability by 92%. Resolved coding problems, optimized code performance, addressed 80% of bottlenecks, developed high-quality source code.

DATA SCIENCE INTERN

ALPHAA AI
Sep, 2023 - Dec, 2023 3 months
    Engineered a random forest classifier for customer churn prediction, achieving 85% accuracy. Modeled and analyzed risk tools like VaR and stress tests. Engaged with trading teams for risk and performance studies.

SOFTWARE DEVELOPER INTERN

AITA
May, 2023 - Jul, 2023 2 months
    Engineered an online enrollment system, facilitating registration for over 55+ students nationwide.

Achievements

  • 92% improvement in AI-generated code readability
  • 85% accuracy rate on customer churn prediction
  • 20% reduction in maintenance costs
  • 15% increase in machinery uptime
  • 30% boost in customer satisfaction scores
  • Mean Absolute Error (MAE) of less than 2% in stock price forecasting

Major Projects

4Projects

Predictive Maintenance for Industrial Machinery

    Developed a predictive maintenance solution using LSTM neural networks.

Sentiment Analysis for Customer Feedback

    Implemented Bidirectional LSTM and CNN models for sentiment analysis of movie reviews. Achieved up to 88.61% accuracy with BiLSTM using dropout regularization.

Stock Price Forecasting using Machine Learning

    Applied Random Forest and Gradient Boosting for accurate stock price prediction.

SMART POWER ALLOCATION SYSTEM

    Designed an actor-critic reinforcement learning framework improving power supply reliability by 89%. Achieved 85% faster convergence through novel optimization techniques.

Education

  • Bachelors in Technology ELECTRONICS AND COMMUNICATION ENGINEERING

    INDIAN INSTITUTE OF INFORMATION TECHNOLOGY ALLAHABAD (2024)

  • CBSE CLASS XII

    ST. PAUL HIGH SECONDARY (2019)

Certifications

  • Microsoft Technology Associate (MTA)

  • Microsoft Technology Associate (MTA)

  • Supervised machine learning

  • Advanced in data science

  • Advanced in machine learning

  • Microsoft technology